Search Results for "data capture framework" - Page 5
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Showing 158 open source projects for "data capture framework"
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Graph Nets library
Build Graph Nets in Tensorflow
Graph Nets, developed by Google DeepMind, is a Python library designed for constructing and training graph neural networks (GNNs) using TensorFlow and Sonnet. It provides a high-level, flexible framework for building neural architectures that operate directly on graph-structured data. A graph network takes graphs as inputs, consisting of edges, nodes, and global attributes, and produces updated graphs with modified feature representations at each level. This library implements the foundational ideas from DeepMind’s paper “Relational Inductive Biases, Deep Learning, and Graph Networks”, offering tools to explore relational reasoning and message-passing neural networks. ... -
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LimeReport
Report generator for Qt Framework
...As a data source developer can use SQL database or data passed from application using QAbstractTableModel interface. Besides one can initialize variables which available as database request parameters. LimeReport goal is to provide your application with functionaly abundant and at the same time simple to use tool for a report generation to be used even by inexperienced in IT users. -
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easy_profiler
Lightweight profiler library for c++
Lightweight cross-platform profiler library for C++. You can profile any function in your code. Furthermore, this library provides measuring time of any block of code. For example, information for 12 millions of blocks is using less than 300Mb of memory. Working profiler slows your application execution for only 1-2%. The average overhead per block is about 15ns/block (tested on Intel Core i7-5930K 3.5GHz, Win7). Disabled profiler will not affect your application execution in any way. You... -
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Incremental DOM
An in-place DOM diffing library
...It integrates naturally with template compilers (such as those that generate calls from HTML-like markup) but can also be used by hand for fine-tuned rendering. The library is small and focused: it manages element creation, attribute updates, and text nodes while leaving state management and data flow to the host framework. The result is predictable updates with minimal overhead, especially useful in performance-critical views. -
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I3D models trained on Kinetics
Convolutional neural network model for video classification
...The project provides TensorFlow and Sonnet-based implementations, pretrained checkpoints, and example scripts for evaluating or fine-tuning models. It also offers sample data, including preprocessed video frames and optical flow arrays, to demonstrate how to run inference and visualize outputs. -
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benchm-ml
A benchmark of commonly used open source implementations
This repository is designed to provide a minimal benchmark framework comparing commonly used machine learning libraries in terms of scalability, speed, and classification accuracy. The focus is on binary classification tasks without missing data, where inputs can be numeric or categorical (after one-hot encoding). It targets large scale settings by varying the number of observations (n) up to millions and the number of features (after expansion) to about a thousand, to stress test different implementations. ... -
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JSVerbalExpressions
JavaScript Regular expressions made easy
VerbalExpressions is a JavaScript library that helps to construct difficult regular expressions. Methods have a return type of VerbalExpression except where mentioned otherwise. If there is no mention of a method’s parameters, it is to be assumed that it has none. VerEx is the function that is exported from within VerbalExpressions.js and is to be the first method in chains that describe verbal expressions. Construct and return a new instance of VerbalExpression. Used to support the new... -
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TenorSpace.js
Neural network 3D visualization framework
...After preprocessing the model, TensorSpace supports the visualization of pre-trained models from TensorFlow, Keras and TensorFlow.js. TensorSpace is a neural network 3D visualization framework designed for not only showing the basic model structure but also presenting the processes of internal feature abstractions, intermediate data manipulations and final inference generations. By applying TensorSpace API, it is more intuitive to visualize and understand any pre-trained models built by TensorFlow, Keras, TensorFlow.js, etc. -
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Django REST Pandas
Serves up Pandas dataframes via the Django REST Framework
Django REST Pandas (DRP) provides a simple way to generate and serve pandas DataFrames via the Django REST Framework. The resulting API can serve up CSV (and a number of other formats for consumption by a client-side visualization tool like d3.js. The design philosophy of DRP enforces a strict separation between data and presentation. This keeps the implementation simple, but also has the nice side effect of making it trivial to provide the source data for your visualizations. ... -
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PHPExcel
Library offering classes to read from and write to spreadsheet formats
PHPExcel is a comprehensive library for reading, writing, and manipulating Excel spreadsheets in PHP, supporting multiple formats like XLS, XLSX, CSV, and more. Developers can create complex spreadsheets with styled cells, formulas, charts, images, and multiple sheets programmatically. It also supports reading existing files, iterating through cells, applying data validation, and converting between formats. Because it handles the details of Excel file structures—including relationships,... -
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SFD
S³FD: Single Shot Scale-invariant Face Detector, ICCV, 2017
S³FD (Single Shot Scale-invariant Face Detector) is a real-time face detection framework designed to handle faces of various sizes with high accuracy using a single deep neural network. Developed by Shifeng Zhang, S³FD introduces a scale-compensation anchor matching strategy and enhanced detection architecture that makes it especially effective for detecting small faces—a long-standing challenge in face detection research. The project builds upon the SSD framework in Caffe, with... -
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Skater
Python library for model interpretation/explanations
Skater is a unified framework to enable Model Interpretation for all forms of the model to help one build an Interpretable machine learning system often needed for real-world use-cases(** we are actively working towards to enabling faithful interpretability for all forms models). It is an open-source python library designed to demystify the learned structures of a black box model both globally(inference on the basis of a complete data set) and locally(inference about an individual prediction). ... -
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FlexibleParser_Java
Group of multi-purpose Java-converted-from-C# parsing libraries.
FlexibleParser (Java) is currently formed by the following independent libraries/parts: - UnitParser. It allows to easily deal with a wide variety of situations involving units of measurement. - NumberParser. It provides a common framework for all the .NET numeric types. AUTHORSHIP & COPYRIGHT I, Alvaro Carballo Garcia (varocarbas), am the sole author of each single bit of this code. All the contents of this repository can be considered public domain. For more information about my... -
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FlexibleParser
FlexibleParser is a group of multi-purpose .NET parsing libraries.
FlexibleParser (C#/.NET) is currently formed by the following independent libraries/parts: - UnitParser. It allows to easily deal with a wide variety of situations involving units of measurement. - NumberParser. It provides a common framework for all the .NET numeric types. - DateParser. It enhances the default .NET date/time support. AUTHORSHIP & COPYRIGHT I, Alvaro Carballo Garcia (varocarbas), am the sole author of each single bit of this code. All the contents of this... -
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UltraPlugin.js
A smart framework to developing sites and web applications
[This project has been discontinued but you can use ALL versions created] UltraPlugin.js is the ultra smart powerful union of a data library containing a large proportion of functions that allows the user to develop web sites and applications in a pleasant and fast way with a framework that creates several possibilities by joining Html, Css and Visual Basic Script with the JS itself and allowing several new types of elements. This project is totally open-source and has a natural development so that users can adapt the work to their own way, besides being able to contribute with the author, warning bugs, faults or even possible improvements. ... -
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ideabook
A growth engineering idea in action
...Each project is described with background, a showcase or story of need, and step-by-step implementation suggestions: from building a GIS system with Django+Haystack, to an editing-publishing separated blogging system, to an Ionic/Electron hybrid application, to building a JavaScript slide framework. The aim is to give developers concrete, creative, and tricky exercise ideas rather than generic “todo app” templates, helping them build their portfolio, sharpen skills, and explore architectures. The repository emphasizes “growth engineering”, building systems, not just UI, that require thinking about data flows, tooling, deployment, and scaling. ... -
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EaselJS
Work with the HTML5 Canvas element easily
The Easel Javascript library provides a full, hierarchical display list, a core interaction model, and helper classes to make working with the HTML5 Canvas element much easier. A JavaScript library that makes working with the HTML5 Canvas element easy. Useful for creating games, generative art, and other highly graphical experiences. EaselJS provides straight forward solutions for working with rich graphics and interactivity with HTML5 Canvas. It provides an API that is familiar to Adobe... -
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torch-rnn
Efficient, reusable RNNs and LSTMs for torch
The torch-rnn project is a lightweight and efficient implementation of recurrent neural networks built on the Torch framework, focusing on flexibility and reusability for sequence modeling tasks. It provides implementations of standard RNNs and long short-term memory networks, enabling users to train models for tasks such as text generation, language modeling, and sequence prediction. The repository emphasizes simplicity and performance, offering a streamlined pipeline for preprocessing data, training models, and sampling outputs. ... -
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Trivial Serialization Library
C++11 serialization library
Trivial Serialization Library (TSL) is a simple C++11 framework for object [de]serialization. -
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MEAN
For simple and scalable fullstack js applications
...The mean stack is intended to provide a simple and fun starting point for cloud native fullstack javascript applications. MEAN is a set of Open Source components that together, provide an end-to-end framework for building dynamic web applications; starting from the top (code running in the browser) to the bottom (database). The stack is made up of MongoDB, with document database, used by your back-end application to store its data as JSON (JavaScript Object Notation) documents. Also with Express (sometimes referred to as Express.js), with back-end web application framework running on top of Node.js. ... -
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Random Bits Forest
RBF: a Strong Classifier/Regressor for Big Data
...It first generates and selects ~10,000 small three-layer threshold random neural networks as basis by gradient boosting scheme. These binary basis are then feed into a modified random forest algorithm to obtain predictions. In conclusion, RBF is a novel framework that performs strongly especially on data with large size. -
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Question Answering Corpus
Question answering dataset in "Teaching Machines to Read & Comprehend"
RC-Data is a dataset generation framework created by Google DeepMind to produce large-scale reading comprehension question-answer pairs from CNN and Daily Mail news articles. The dataset, introduced in the 2015 paper “Teaching Machines to Read and Comprehend” (Hermann et al., NIPS 2015), was among the first large corpora designed to train and evaluate machine reading and comprehension models. -
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Sesame
Java RDF Framework
This project is no longer actively maintained. It is succeeded by the Eclipse RDF4J project, which can be found at GitHub and at http://www.rdf4j.org/. Sesame is a de-facto standard framework for processing RDF data. This includes parsing, scalable storage, reasoning and full SPARQL 1.1 query/update support. Sesame offers a fully modular toolkit and an easy-to-use Java API that can be connected to all leading RDF storage solutions. -
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Webiness
Lightweight PHP framework
Webiness is lightweight PHP framework based on MVC design pattern. It has a very straightforward installation process that requires only a minimal configuration, so it can save you a lot of hassle. Also, it canbe an ideal choice if you want to avoid PHP version conflict, as it works on all PHP versions from 5.3. Webiness extensively uses the lazy loading technique so, in most cases, it is faster then other frameworks. It can be used for rapid prototyping of web applications. Webiness is... -
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dotNetRDF is a .Net Class Library for working with RDF and SPARQL programatically built with C# 3 for the .Net Framework 3.5/4.0/Silverlight 4 and WIndows Phone 7. It provides a simple object model for representing RDF, SPARQL Queries and Updates and understands all common RDF and SPARQL syntaxes. Extensive documentation is available on the website and support is available via the mailing lists.
